9780262538701 - probabilistic machine learning for civil engineers (the mit press) de goulet, james-a. (17 resultados)
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Librería: Books Puddle, New York, Estados Unidos de AmericaBooks Puddle
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EUR 42,07
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Condición: New. pp. 304.
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Librería: GreatBookPrices, Columbia, Estados Unidos de AmericaGreatBookPrices
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EUR 55,54
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Librería: Rarewaves USA, OSWEGO, Estados Unidos de AmericaRarewaves USA
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EUR 57,91
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Paperback. Condición: New.
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Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
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EUR 50,54
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Condición: New. pp. 304.
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Librería: SMASS Sellers, IRVING, Estados Unidos de AmericaSMASS Sellers
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EUR 59,44
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Condición: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.
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Librería: Biblios, frankfurt am main, AlemaniaBiblios
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EUR 49,67
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Condición: New. pp. 304.
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Librería: WorldofBooks, Goring-By-Sea, Reino UnidoWorldofBooks
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EUR 54,81
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Paperback. Condición: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
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Librería: Grand Eagle Retail, Bensenville, Estados Unidos de AmericaGrand Eagle Retail
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EUR 63,39
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Paperback. Condición: new. Paperback. An introduction to key concepts and techniques in probabilistic machine learning for civil engineering students and professionals; with many step-by-step examples, illustrations, and exercises.This book introduces probabilistic machine learning concepts to civil engineering students and prof…essionals, presenting key approaches and techniques in a way that is accessible to readers without a specialized background in statistics or computer science. It presents different methods clearly and directly, through step-by-step examples, illustrations, and exercises. Having mastered the material, readers will be able to understand the more advanced machine learning literature from which this book draws.The book presents key approaches in the three subfields of probabilistic machine learning- supervised learning, unsupervised learning, and reinforcement learning. It first covers the background knowledge required to understand machine learning, including linear algebra and probability theory. It goes on to present Bayesian estimation, which is behind the formulation of both supervised and unsupervised learning methods, and Markov chain Monte Carlo methods, which enable Bayesian estimation in certain complex cases. The book then covers approaches associated with supervised learning, including regression methods and classification methods, and notions associated with unsupervised learning, including clustering, dimensionality reduction, Bayesian networks, state-space models, and model calibration. Finally, the book introduces fundamental concepts of rational decisions in uncertain contexts and rational decision-making in uncertain and sequential contexts. Building on this, the book describes the basics of reinforcement learning, whereby a virtual agent learns how to make optimal decisions through trial and error while interacting with its environment. An introduction to key concepts and techniques in probabilistic machine learning for civil engineering students and professionals; with many step-by-step examples, illustrations, and exercises. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Librería: GreatBookPrices, Columbia, Estados Unidos de AmericaGreatBookPrices
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EUR 62,71
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Condición: As New. Unread book in perfect condition.
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Librería: Kennys Bookshop and Art Galleries Ltd., Galway, IrlandaKennys Bookshop and Art Galleries Ltd.
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EUR 70,68
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Condición: New. 2020. Illustrated. Paperback. . . . . .
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- Edición internacional
Librería: UK BOOKS STORE, London, Reino UnidoUK BOOKS STORE
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EUR 89,11
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Paperback. Condición: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 7-12 days and we do have flat rate for up to 2LB. Extra shipping charges will be requ…ested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
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Librería: Kennys Bookstore, Olney, Estados Unidos de AmericaKennys Bookstore
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EUR 87,26
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Condición: New. 2020. Illustrated. Paperback. . . . . . Books ship from the US and Ireland.
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Librería: Rarewaves USA United, OSWEGO, Estados Unidos de AmericaRarewaves USA United
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EUR 59,78
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Paperback. Condición: New.
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Librería: Rarewaves.com UK, London, Reino UnidoRarewaves.com UK
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EUR 57,58
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Paperback. Condición: New.
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Librería: AussieBookSeller, Truganina, AustraliaAussieBookSeller
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EUR 108,51
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Paperback. Condición: new. Paperback. An introduction to key concepts and techniques in probabilistic machine learning for civil engineering students and professionals; with many step-by-step examples, illustrations, and exercises.This book introduces probabilistic machine learning concepts to civil engineering students and prof…essionals, presenting key approaches and techniques in a way that is accessible to readers without a specialized background in statistics or computer science. It presents different methods clearly and directly, through step-by-step examples, illustrations, and exercises. Having mastered the material, readers will be able to understand the more advanced machine learning literature from which this book draws.The book presents key approaches in the three subfields of probabilistic machine learning- supervised learning, unsupervised learning, and reinforcement learning. It first covers the background knowledge required to understand machine learning, including linear algebra and probability theory. It goes on to present Bayesian estimation, which is behind the formulation of both supervised and unsupervised learning methods, and Markov chain Monte Carlo methods, which enable Bayesian estimation in certain complex cases. The book then covers approaches associated with supervised learning, including regression methods and classification methods, and notions associated with unsupervised learning, including clustering, dimensionality reduction, Bayesian networks, state-space models, and model calibration. Finally, the book introduces fundamental concepts of rational decisions in uncertain contexts and rational decision-making in uncertain and sequential contexts. Building on this, the book describes the basics of reinforcement learning, whereby a virtual agent learns how to make optimal decisions through trial and error while interacting with its environment. An introduction to key concepts and techniques in probabilistic machine learning for civil engineering students and professionals; with many step-by-step examples, illustrations, and exercises. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Editorial: Penguin Random House
Librería: INDOO, Avenel, Estados Unidos de AmericaINDOO
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EUR 49,47
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Condición: As New. Unread copy in mint condition.
Editorial: Penguin Random House
Librería: INDOO, Avenel, Estados Unidos de AmericaINDOO
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 49,56
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Condición: New. Brand New.
